CS X459.33 - Unsupervised Machine Learning: Clustering and Association Rules with Python

Course Description

This course introduces the concepts of supervised and unsupervised machine learning, focusing on the more well-known unsupervised method, clustering. Explore cluster analyses methods, such as k-means and hierarchical clustering for classifying data. Additional topics covered include the association rules using the Apriori Algorithm for data mining in Python, and detecting patterns and frequent item sets within the data.

Prerequisites

CS X459.30 - Introduction to Python, Data Preparation, and Visualization (Pass)